Fortunately, Namaste Tech is very committed to protecting the privacy of its employees. It has developed the “My Namaste” App based on the zkPass Proof-as-a-Service architecture, which allows third-party entities to examine users’ information without compromising confidential information.
Taking the Proof Verifier role, Namaste Tech needs to create a DVR to query the blood test results of the incoming new employee.
Namaste Tech defines the “Employee Onboarding” DVR Query for user Jane Doe as follows:
Do all of the following conditions hold true?
Is the lab's ID exactly "QH801874"?
Is the test ID exactly "SCREEN-7083-12345"?
Does the subject's first name match "jane" (case insensitive) ?
Does the subject's last name match "doe" (case insensitive) ?
Is the subject's date of birth exactly "1985-12-12"?
Is the level of amphetamines measured in panels (in Ng/mL) exactly zero?
Is the level of cocaine measured in panels (in Ng/mL) equal to or less than 10?
[
{
"assign": {
"blood_test_status": {
"and": [
{
"==": [{ "dvar": "lab.ID" }, "QH801874"]
},
{
"==": [{ "dvar": "testID" }, "SCREEN-7083-12345"]
},
{
"~==": [{ "dvar": "subject.firstName" }, "jane"]
},
{
"~==": [{ "dvar": "subject.lastName" }, "doe"]
},
{
"==": [{ "dvar": "subject.dateOfBirth" }, "1985-12-12"]
},
{
"==": [{ "dvar": "measuredPanelsNgML.amphetamines" }, 0]
},
{
"<=": [{ "dvar": "measuredPanelsNgML.cocaine" }, 10]
}
]
}
}
},
{ "output": { "title": "Blood Test Result" } },
{ "output": { "result": { "lvar": "blood_test_status" } } },
{ "output": { "name": { "dvar": "subject.firstName" } } }
]